Senior Machine Learning Engineer - Multimodal Data
Vienna, Vienna, Austria
EUR 70K-70K (estimate) Senior-level Full Time
Tasks
- Build and maintain data loading storage and retrieval infrastructure
- Build validation frameworks and monitor data quality for drift and contamination
- Collect preference data for RLHF and DPO style training
- Create evaluation datasets and benchmarks
- Design and build data pipelines for agent training
- Develop dataset construction tooling including annotation workflows and synthetic data generation
- Document dataset provenance known limitations intended use cases and version history
- Identify data bottlenecks and propose solutions
- Implement test coverage for data pipelines and ML workflows
- Perform code reviews and refactor to improve codebase quality
- Translate research requirements into data specifications
Perks/Benefits
Skills/Tech-stack
AWS | Amazon S3 | Annotation tools | Batching | Contamination detection | DPO | Data Contamination Detection | Data Drift | Data Drift Detection | Data Pipelines | Data Quality | Data Retrieval | Data Storage | Data Versioning | Data loading | Data quality monitoring | Distributed Systems | Drift Detection | Fine Tuning | Human-in-the-loop | LLM Fine-tuning | Label Studio | Language Models | Large Language Models | Machine Learning | Multimodal Data | Prompt engineering | Python | Quality monitoring | RLHF | Ray | Reward Modeling | Sharding | Streaming Pipelines | Synthetic data | The Loop | Tokenization | Vision Language Models | Vision-language
Education
N/A
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